Data Science Blog

JULY 20, 2024

Die Bedeutung effizienter und zuverlässiger Datenpipelines in den Bereichen Data Science und Data Engineering ist enorm. Vielfältige Unterstützung: Kompatibel mit verschiedenen Datenbankmanagementsystemen wie MS SQL Server und Azure Synapse Analytics. Data Lakes: Unterstützt MS Azure Blob Storage.

Azure 130

Azure Power BI SQL Data Lakes 130

ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

Data Science 101

NOVEMBER 11, 2019

Welcome to the first beta edition of Cloud Data Science News. This will cover major announcements and news for doing data science in the cloud. Microsoft Azure. Azure Arc You can now run Azure services anywhere (on-prem, on the edge, any cloud) you can run Kubernetes. Amazon Web Services.

Cloud Data 95

Cloud Data Data Science Azure Clustering 95

Data Science 101

NOVEMBER 7, 2019

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Azure Synapse. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Azure Quantum.

Data Science 106

Data Science Azure SQL Machine Learning 106

ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Well, these libraries will give you a solid start.

Data Lakes 52

Data Lakes ML ML Citizen Data Scientist 52

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Data Science 101

DECEMBER 16, 2019

Even though Amazon is taking a break from announcements (probably focusing on Christmas shoppers), there are still some updates in the cloud data science world. Azure Database for MySQL now supports MySQL 8.0 This is the latest major version of MySQL Azure Functions 3.0 Azure Database for MySQL now supports MySQL 8.0

Cloud Data 81

Cloud Data Data Science Azure Natural Language Processing 81

phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

ODSC - Open Data Science

MAY 8, 2023

Article on Azure ML by Bethany Jepchumba and Josh Ndemenge of Microsoft In this article, I will cover how you can train a model using Notebooks in Azure Machine Learning Studio. When uploading your data, you specify the Machine Learning type, test, and training data before training. Let us get started!

Azure 52

Azure ML ML Data Models 52

ODSC - Open Data Science

FEBRUARY 2, 2023

Here’s what we found for both skills and platforms that are in demand for data scientist jobs. Data Science Skills and Competencies Aside from knowing particular frameworks and languages, there are various topics and competencies that any data scientist should know. Joking aside, this does infer particular skills.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

Mlearning.ai

JULY 8, 2023

One of them is Azure functions. In this article we’re going to check what is an Azure function and how we can employ it to create a basic extract, transform and load (ETL) pipeline with minimal code. A batch ETL works under a predefined schedule in which the data are processed at specific points in time.

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ETL Azure Python Internet of Things 52

Data Science Blog

FEBRUARY 7, 2023

Für Data Science ja sowieso. Was gerade zum Trend wird, ist der Aufbau eines Data Lakehouses. Ein Lakehouse inkludiert auch clevere Art und Weise auch einen Data Lake. Die Inhalte des Data Lakes sind bestenfalls etwas vorsortiert, aber eigentlich hofft man ja nicht, da wieder irgendwas drin wiederfinden zu müssen.

Business Intelligence 286

Business Intelligence Business Intelligence Data Warehouse Data Lakes 286

ODSC - Open Data Science

JANUARY 18, 2024

These professionals will work with their colleagues to ensure that data is accessible, with proper access. So let’s go through each step one by one, and help you build a roadmap toward becoming a data engineer. Identify your existing data science strengths. Stay on top of data engineering trends.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Dataconomy

JUNE 1, 2023

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. OneLake is designed to store a single copy of data in a unified location, leveraging the open-source Apache Parquet format.

Power BI 194

Power BI Data Lakes Azure Data Silos 194

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. DataRobot is available on Azure as an AI Platform Single-Tenant SaaS, eliminating the time and cost of an on-premises implementation.

Azure 59

Azure Machine Learning Machine Learning AI 59

ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

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Azure ML ML Data Modeling 52

Dataversity

JULY 9, 2021

blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source DevOps on the cloud with protected internal legacy tools, SQL with NoSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […]. The post Will They Blend?

Azure 52

Azure Data Lakes SQL ML 52

Data Science Dojo

SEPTEMBER 11, 2024

With this full-fledged solution, you don’t have to spend all your time and effort combining different services or duplicating data. Overview of One Lake Fabric features a lake-centric architecture, with a central repository known as OneLake. Now, we can save the data as delta tables to use later for sales analytics.

Power BI 195

Power BI Data Pipeline Data Warehouse Data Engineer 195

ODSC - Open Data Science

OCTOBER 25, 2024

Delphina Demo: AI-powered Data Scientist Jeremy Hermann | Co-founder at Delphina | Delphina.Ai In this demo, you’ll see how Delphina’s AI-powered “junior” data scientist can transform the data science workflow, automating labor-intensive tasks like data discovery, transformation, and model building.

AI 52

AI AI Data Scientist Data Lakes 52

DagsHub

DECEMBER 11, 2023

The following points illustrates some of the main reasons why data versioning is crucial to the success of any data science and machine learning project: Storage space One of the reasons of versioning data is to be able to keep track of multiple versions of the same data which obviously need to be stored as well.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Database 98

ODSC - Open Data Science

APRIL 27, 2023

5 Data Engineering and Data Science Cloud Options for 2023 AI development is incredibly resource intensive. As such, here are a few data science cloud options to help you handle some work virtually. Here are a few things to keep an eye out for. What are the benefits of this technology, and how can you apply it?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

ODSC - Open Data Science

OCTOBER 3, 2024

AI and Data: Enhancing Development with GitHub Copilot How can GitHub Copilot be used in environments like Visual Studio Code, JetBrains IDEs, or Azure Data Studio to significantly reduce coding time? Industry, Opinion, Career Advice AI for Robotics and Autonomy with Francis X.

Data Science 40

Data Science Data Lakes Data Scientist AI 40

Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

ODSC - Open Data Science

JULY 22, 2023

The week was filled with engaging sessions on top topics in data science, innovation in AI, and smiling faces that we haven’t seen in a while. On Wednesday, Henk Boelman, Senior Cloud Advocate at Microsoft, spoke about the current landscape of Microsoft Azure, as well as some interesting use cases and recent developments.

Apache Kafka 52

Apache Kafka Machine Learning Machine Learning Data Science 52

ODSC - Open Data Science

AUGUST 24, 2023

ODSC West Call for Volunteers October 30th to November 2nd Our Volunteer program is a great way to get involved in ODSC — one of the world’s largest conferences and communities of artificial intelligence and data science experts. With that comes the need for new skills and new strategies to get interviews.

Data Lakes 52

Data Lakes Data Science Machine Learning Machine Learning 52

ODSC - Open Data Science

APRIL 3, 2023

As the sibling of data science, data analytics is still a hot field that garners significant interest. Companies have plenty of data at their disposal and are looking for people who can make sense of it and make deductions quickly and efficiently. Cloud Services: Google Cloud Platform, AWS, Azure.

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Analytics Analytics Data Analyst Data Science 52

ODSC - Open Data Science

JUNE 12, 2023

Power BI Datamarts provide no-code/low-code datamart capabilities using Azure SQL Database technology in the background. The Power BI Datamarts support sensitivity labels, endorsement, discovery, and Row-Level Security ( RLS ), which help protect and manage the data according to the business requirements and compliance needs.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

ODSC - Open Data Science

OCTOBER 20, 2023

At the AI Expo and Demo Hall as part of ODSC West in a few weeks, you’ll have the opportunity to meet one-on-one with representatives from industry-leading organizations like Microsoft Azure, Hewlett Packard, Iguazio, neo4j, Tangent Works, Qwak, Cloudera, and others. LLMs in Data Analytics: Can They Match Human Precision?

AI 52

AI AI Data Science Machine Learning 52

ODSC - Open Data Science

JULY 11, 2023

Co-location data centers: These are data centers that are owned and operated by third-party providers and are used to house the IT equipment of multiple organizations. Edge data centers: These are data centers that are located closer to the edge of the network, where data is generated and consumed, rather than in central locations.

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

The MLOps Blog

JANUARY 23, 2023

These tools may have their own versioning system, which can be difficult to integrate with a broader data version control system. For instance, our data lake could contain a variety of relational and non-relational databases, files in different formats, and data stored using different cloud providers. DVC Git LFS neptune.ai

ML 52

ML ML Data Lakes Machine Learning 52

The MLOps Blog

JUNE 27, 2023

Microsoft Azure ML Platform The Azure Machine Learning platform provides a collaborative workspace that supports various programming languages and frameworks. DataRobot MLOps facilitates collaboration between data scientists, data engineers, and IT operations, ensuring smooth integration of models into the production environment.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Dataconomy

SEPTEMBER 4, 2023

Data integration: Integrate data from various sources into a centralized cloud data warehouse or data lake. Ensure that data is clean, consistent, and up-to-date. Use ETL (Extract, Transform, Load) processes or data integration tools to streamline data ingestion.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

O'Reilly Media

OCTOBER 19, 2021

Similarly, it would be pointless to pretend that a data-intensive application resembles a run-off-the-mill microservice which can be built with the usual software toolchain consisting of, say, GitHub, Docker, and Kubernetes. Adapted from the book Effective Data Science Infrastructure. Data Science Layers.

ML 140

ML ML Data Scientist AWS 140

Mlearning.ai

FEBRUARY 16, 2023

The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data. The solution was built on top of Amazon Web Services and is now available on Google Cloud and Microsoft Azure. If you’re already utilizing any software to work with data, you can check which options Snowflake provides.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

The MLOps Blog

OCTOBER 20, 2023

Jupyter notebooks have been one of the most controversial tools in the data science community. Nevertheless, many data scientists will agree that they can be really valuable – if used well. I’ll show you best practices for using Jupyter Notebooks for exploratory data analysis. Aside neptune.ai

SQL 52

SQL Database Data Scientist Python 52

phData

SEPTEMBER 20, 2023

A data mesh is a conceptual architectural approach for managing data in large organizations. Traditional data management approaches often involve centralizing data in a data warehouse or data lake, leading to challenges like data silos, data ownership issues, and data access and processing bottlenecks.

Data Silos 52

Data Silos Database Data Quality Data Engineer 52

Alation

APRIL 14, 2022

This two-part series will explore how data discovery, fragmented data governance , ongoing data drift, and the need for ML explainability can all be overcome with a data catalog for accurate data and metadata record keeping. The Cloud Data Migration Challenge.

Data Governance 59

Data Governance ML ML Cloud Data 59